2025
What Should Health Professions Students Learn About Data Bias?
Shenson D, Sheares B, Fearce C. What Should Health Professions Students Learn About Data Bias? The AMA Journal Of Ethic 2025, 27: e14-20. PMID: 39745910, DOI: 10.1001/amajethics.2025.14.Peer-Reviewed Original Research
2023
Harnessing the power of synthetic data in healthcare: innovation, application, and privacy
Giuffrè M, Shung D. Harnessing the power of synthetic data in healthcare: innovation, application, and privacy. Npj Digital Medicine 2023, 6: 186. PMID: 37813960, PMCID: PMC10562365, DOI: 10.1038/s41746-023-00927-3.Peer-Reviewed Original ResearchDifferential privacySynthetic dataPredictive analyticsReal-world healthcare applicationDigital twin technologyData privacyData integrityPrivacy concernsTwin technologyData misuseHealthcare applicationsPrivacyData biasDifferent applicationsData qualityAnalyticsAlgorithmic tradingAnalytic contextApplicationsHealthcareTraceabilityDatasetEmergent fieldPropose strategiesPortfolio optimizationVicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation
Huang Y, Xie W, Li M, Cheng M, Wu J, Wang W, You J, Liu X. Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation. Lecture Notes In Computer Science 2023, 13939: 360-371. DOI: 10.1007/978-3-031-34048-2_28.Peer-Reviewed Original ResearchFederated learningData augmentationFeature statisticsDeep learningAvailability of labeled dataPerformance of FLPrivacy protectionGeneralization capabilityData distributionMedical segmentationGaussian prototypeCollaborative trainingFL methodsFeature shiftsMinimization perspectiveAugmented scopeRaw dataCardiac segmentsGaussian distributionVolume segmentationData biasDiscrepancy of dataDataLearningMixupNetwork embedding unveils the hidden interactions in the mammalian virome
Poisot T, Ouellet M, Mollentze N, Farrell M, Becker D, Brierley L, Albery G, Gibb R, Seifert S, Carlson C. Network embedding unveils the hidden interactions in the mammalian virome. Patterns 2023, 4: 100738. PMID: 37409053, PMCID: PMC10318366, DOI: 10.1016/j.patter.2023.100738.Peer-Reviewed Original ResearchMammalian viromeViral genomic featuresHost-virus interactionsGraph embeddingGenomic featuresNetwork science problemUnder-characterizedFundamental biologyHuman infectionsViromeRecommender systemsDiscovery effortsAmazon basinDisease emergenceHidden interactionsImputation algorithmData biasNetworkLinear filterScience problems
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